A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications

BACKGROUND: A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify sept...

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Detalles Bibliográficos
Autores principales: Zheng, Yongxin, Wang, Jinping, Ling, Zhaoyi, Zhang, Jiamei, Zeng, Yuan, Wang, Ke, Zhang, Yu, Nong, Lingbo, Sang, Ling, Xu, Yonghao, Liu, Xiaoqing, Li, Yimin, Huang, Yongbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498641/
https://www.ncbi.nlm.nih.gov/pubmed/37700323
http://dx.doi.org/10.1186/s12967-023-04499-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498641/
https://www.ncbi.nlm.nih.gov/pubmed/37700323
http://dx.doi.org/10.1186/s12967-023-04499-4

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